Gemini 3 Deep Think Is INCREDIBLE! World's Greatest AI Model EVER! (Tested)

Gemini 3 Deepthink Model: A Detailed Overview

Key Concepts: Gemini 3 Deepthink, Chain-of-Thought Reasoning, AGI (Artificial General Intelligence), ELO (rating system), ARK AGI 2 Benchmark, API (Application Programming Interface), SVG (Scalable Vector Graphics), Decentralized Power Grid Simulation.

I. Introduction of Gemini 3 Deepthink

Google recently released the Gemini 3 Deepthink model, described as their most specialized reasoning model to date and, according to the speaker, the smartest AI model currently available. This variant is specifically optimized for complex, multi-step reasoning, particularly in fields like science, mathematics, research, engineering, coding, and open-ended technical problem-solving. The speaker emphasizes its exceptional capabilities, stating it’s the smartest model they’ve personally used.

II. Performance and Benchmarks

Deepthink demonstrates remarkable performance across various benchmarks:

• Humanity's Last Exam: Achieved approximately 48% without tool use.
• Codeforces ELO: Reached a staggering 3,455 ELO, showcasing strong coding abilities.
• ARK AGI 2: Scored 84.6, surpassing the human baseline and indicating a significant breakthrough in AI reasoning, particularly in visual logic puzzles. This result is verified by the ARK Prize Foundation and is seen as a step towards AGI.
• PhD-Level Math: Excels at identifying subtle logical errors in advanced mathematical papers.

III. Demonstrations and Real-World Applications

The video showcases several impressive applications of the Deepthink model:

• Sketch to 3D Model: Successfully converts hand-drawn sketches into 3D printable models, a task where most other models fail. The model analyzes the drawing, creates a model, and generates a file for 3D printing.
• Minecraft Clone Generation: Two Minecraft clones were generated. Ken’s version, created with Deepthink, is highlighted for its advanced features including sound effects, block punching, item collection, crafting inventory, and functional block placement. The speaker’s own attempt, while functional, was less polished, emphasizing the importance of detailed prompting.
• Mac OS Clone: Generated a remarkably accurate browser-based Mac OS clone, mimicking the appearance and functionality of the operating system, including Finder, applications (Notes, Calculator, Settings), and even customizable appearance settings.
• Landing Page Generation: Created a modern, minimal landing page with dynamic animations, smooth scrolling, and micro-interactions, surpassing the capabilities of previous models like Gemini 3 Pro.
• 3D Model of a PS5 Controller: Generated a 3D model of a PS5 controller, though the speaker notes it wasn’t perfect, it demonstrated a decent attempt at replicating the controller’s structure. A 3D animation of an Xbox controller generated by Ken was noted as superior, likely due to better prompting.
• Autonomous Planet Ecosystem Simulation: Designed and coded a fully autonomous, vectorized planet ecosystem in Python, featuring thousands of AI-driven plants and animals interacting under realistic climates. This simulation, running in a single HTML file, demonstrates predator-prey dynamics and weather simulation.
• SVG Butterfly Generation: Initial attempts to generate a butterfly in SVG code were underwhelming. However, other users achieved photorealistic results, demonstrating the model’s potential in 2D graphics.
• Decentralized Power Grid Simulator: Built a massive decentralized power grid simulator with thousands of nodes capable of failing, self-healing, and running under real-world performance limits, all within a single Python file. The simulation visualizes cascading faults, heat waves, cyberattacks, and line failures.

IV. Access and Technical Details

• Access: Currently available through the Google AI Ultra subscription, costing approximately $125 for the first three months, then $250/month (USD).
• API Access: An API is forthcoming, with a sign-up available (link in the video description).
• Deepthink Mode Activation: Within the Google AI interface, Deepthink mode is enabled by selecting "Tools" then "Deepthink," offering options for extended reasoning. The "Keep Thinking" option utilizes the pro extended version but takes longer to generate results.

V. Key Arguments and Perspectives

The speaker argues that Gemini 3 Deepthink represents a significant leap forward in AI reasoning capabilities, potentially moving closer to AGI. The model’s ability to handle complex, multi-step problems and surpass human performance on benchmarks like ARK AGI 2 supports this claim. The speaker emphasizes that Deepthink isn’t just about generating code; it’s about thinking through complex engineering problems end-to-end, designing architectures, and handling stability issues.

VI. Notable Quotes

• “This is genuinely Google's smartest and most intelligent model to date.”
• “It’s now beating the human baseline on this test [ARK AGI 2]. Solving most of these visual logic puzzles correctly and this is where a lot of people see this as a huge step towards more genuine general intelligence or something like AGI capabilities.”
• “It is just giving Gemini a way for it to think through extremely complex engineering problems end to end.”

VII. Conclusion

Gemini 3 Deepthink is a powerful and versatile AI model demonstrating exceptional reasoning and problem-solving abilities. While access is currently limited by subscription cost, the model’s performance across diverse tasks – from 3D modeling to complex simulations – positions it as a leading tool in the field of AI. The forthcoming API access promises to broaden its accessibility and impact. The speaker recommends exploring the model if resources allow, highlighting its potential for tackling challenging technical problems.